Integrated analysis of diverse cancer types reveals a breast cancer-specific serum miRNA biomarker through relative expression orderings analysis.

PURPOSE: Serum microRNA (miRNA) holds great potential as a non-invasive biomarker for diagnosing breast cancer (BrC). However, most diagnostic models rely on the absolute expression levels of miRNAs, which are susceptible to batch effects and challenging for clinical transformation. Furthermore, current studies on liquid biopsy diagnostic biomarkers for BrC mainly focus on distinguishing BrC patients from healthy controls, needing more specificity assessment. METHODS: We collected a large number of miRNA expression data involving 8465 samples from GEO, including 13 different cancer types and non-cancer controls. Based on the relative expression orderings (REOs) of miRNAs within each sample, we applied the greedy, LASSO multiple linear regression, and random forest algorithms to identify a qualitative biomarker specific to BrC by comparing BrC samples to samples of other cancers as controls. RESULTS: We developed a BrC-specific biomarker called 7-miRPairs, consisting of seven miRNA pairs. It demonstrated comparable classification performance in our analyzed machine learning algorithms while requiring fewer miRNA pairs, accurately distinguishing BrC from 12 other cancer types. The diagnostic performance of 7-miRPairs was favorable in the training set (accuracy = 98.47%, specificity = 98.14%, sensitivity = 99.25%), and similar results were obtained in the test set (accuracy = 97.22%, specificity = 96.87%, sensitivity = 98.02%). KEGG pathway enrichment analysis of the 11 miRNAs within the 7-miRPairs revealed significant enrichment of target mRNAs in pathways associated with BrC. CONCLUSION: Our study provides evidence that utilizing serum miRNA pairs can offer significant advantages for BrC-specific diagnosis in clinical practice by directly comparing serum samples with BrC to other cancer types.

Senescence-Targeted and NAD+-Dependent SIRT1-Activated Nanoplatform to Counteract Stem Cell Senescence for Promoting Aged Bone Regeneration.

Age-related bone defects are a leading cause of disability and mortality in elderly individuals, and targeted therapy to delay the senescence of bone marrow-derived mesenchymal stem cells (MSCs) has emerged as a promising strategy to rejuvenate bone regeneration in aged scenarios. More specifically, activating the nicotinamide adenine dinucleotide (NAD+)-dependent sirtuin 1 (SIRT1) pathway is demonstrated to effectively counteract MSC senescence and thus promote osteogenesis. Herein, based on an inventively identified senescent MSC-specific surface marker Kremen1, a senescence-targeted and NAD+ dependent SIRT1 activated nanoplatform is fabricated with a dual delivery of resveratrol (RSV) (SIRT1 promoter) and nicotinamide riboside (NR, NAD+ precursor). This targeting nanoplatform exhibits a strong affinity for senescent MSCs through conjugation with anti-Kremen1 antibodies and enables specifically responsive release of NR and RSV in lysosomes via senescence-associated ß-galactosidase-stimulated enzymatic hydrolysis of the hydrophilic chain. Furthermore, this nanoplatform performs well in promoting aged bone formation both in vitro and in vivo by boosting NAD+, activating SIRT1, and delaying MSC senescence. For the first time, a novel senescent MSC-specific surface marker is identified and aged bone repair is rejuvenated by delaying senescence of MSCs using an active targeting platform. This discovery opens up new insights for nanotherapeutics aimed at age-related diseases.

A Decade of Dietary Assessment Methodology Research at the National Institutes of Health, 2012-2021.

BACKGROUND: Assessment of individual and population-level dietary intake is critical for public health surveillance, epidemiology, and dietary intervention research. In recognition of that need, the National Insitutes of Health (NIH) has a history of funding research projects designed to support the development, implementation, and refinement of tools to assess dietary intake in humans. OBJECTIVES: This report provides data and information on NIH-funded dietary intake assessment methodological research over the period of 2012-2021. METHODS: Data were extracted from an internal NIH data system using the Research, Condition, and Disease Categorization (RCDC) spending category for Nutrition. Data were then examined to identify research focused on dietary assessment tools or methods to capture or analyze dietary intake. RESULTS: Over the decade of 2012-2021, NIH supported 46 grants and 2 large contracts specific to dietary assessment methods development. The top 6 Institutes and Offices funding dietary assessment methods research were identified. Most projects were limited to adults. Projects ranged from novel methods to capture dietary intake, and refinement of analytical methods, to biomarkers of dietary intake. One key contract supported the automated self-administered 24-h dietary assessment tool (ASA24), a widely used, free tool available to the research community for assessing dietary intake. CONCLUSIONS: NIH's support for dietary assessment methods development over this 10-y period was small but grew over time with an expanding number and variety of methods, data sources, and technological advancements in the assessment of dietary intake. NIH remains committed to supporting research seeking to advance the field of dietary assessment methods research.

Blood extracellular vesicles carrying synaptic function- and brain-related proteins as potential biomarkers for Alzheimer's disease.

INTRODUCTION: Objective and accessible markers for Alzheimer's disease (AD) and other dementias are critically needed. METHODS: We identified NMDAR2A, a protein related to synaptic function, as a novel marker of central nervous system (CNS)-derived plasma extracellular vesicles (EVs) and developed a flow cytometry-based technology for detecting such plasma EVs readily. The assay was initially tested in our local cross-sectional study to distinguish AD patients from healthy controls (HCs) or from Parkinson's disease (PD) patients, followed by a validation study using an independent cohort collected from multiple medical centers (the Alzheimer's Disease Neuroimaging Initiative). Cerebrospinal fluid AD molecular signature was used to confirm diagnoses of all AD participants. RESULTS: Likely CNS-derived EVs in plasma were significantly reduced in AD compared to HCs in both cohorts. Integrative models including CNS-derived EV markers and AD markers present on EVs reached area under the curve of 0.915 in discovery cohort and 0.810 in validation cohort. DISCUSSION: This study demonstrated that robust and rapid analysis of individual neuron-derived synaptic function-related EVs in peripheral blood may serve as a helpful marker of synaptic dysfunction in AD and dementia.

The potential prognostic and therapeutic application of tissue and circulating microRNAs in cervical cancer.

Cervical cancer (CC) is a common malignancy in women and a major cause of cancer-related mortality globally. Some novel biomarkers may enable the early diagnosis and monitoring of CC. MicroRNAs (miRNAs) are small noncoding RNAs that control gene translation at a posttranscriptional level. Hence the deregulation of these molecules can cause many diseases. There appears to be an association between aberrant miRNA expression and CC, but the molecular mechanisms involved in the development of CC remain unknown. The upregulation of some circulating miRNAs, for example, miRNA-20a, miRNA-203, miRNA-21, miRNA-205, miRNA-218, and miR-485-5, as well as tissue-specific miRNAs, for example, miR-7, miR-10a, miR-17-5p, miR-135b, miR-149, and miR-203 have been found in patients with CC. There is also growing evidence for the importance of miRNAs in the development of drug resistance. This review therefore highlights recently published preclinical and clinical investigation performed on tissue specific and circulating miRNAs, as potential biomarkers for the detection of patients at early stages of CC, in the prediction of prognosis, and monitoring of their response to therapy.

The prognostic and therapeutic application of microRNAs in breast cancer: Tissue and circulating microRNAs.

Breast cancer is the second most common malignancy diagnosed in women, supporting the need for identification of novel prognostic and diagnostic biomarkers. Recently, microRNAs have emerged as molecular regulators that can have key roles in pathogenesis and progression of different malignancies, including breast cancer. Micro-RNAs can be circulated in body fluid, suggesting their values as non-invasive marker. There is growing body of evidence showing the aberrant activation of some known circulating miRNAs, for example let-151a, miR-21, miR-155, miR-,145 miR-18a, miR-16 as well as tissue specific-miRNAs, for example miR-182, miR-145, miR-21, miR-155/154, miR-203, miR-213, miR-7 in patients affected by breast cancer. In addition, there is growing body of evidences on the value of miRNAs to be associated with drug-resistance, suggesting their values as a potential approach to overcome chemo-resistance. Attuned with these facts, this review highlights recent preclinical and clinical investigation performed on tissue-specific miRNAs and circulating as novel promising biomarkers for detection of patients at early stages, prediction of prognosis, and monitoring of the patients in response to therapy.

Polarized HLA Class I Expression on Renal Tubules Hinders the Detection of Donor-Specific Urinary Extracellular Vesicles.

Purpose: Kidney transplantation is the optimal treatment for patients with end-stage kidney disease. Donor-specific urinary extracellular vesicles (uEVs) hold potential as biomarkers for assessing allograft status. We aimed to develop a method for identifying donor-specific uEVs based on human leukocyte antigen (HLA) mismatching with the kidney transplant recipients (KTRs). Patients and Methods: Urine and plasma were obtained from HLA-A2+ donors and HLA-A2- KTRs pre-transplant. CD9 (tetraspanin, EV marker) and HLA-A2 double-positive (CD9+ HLA-A2+) EVs were quantified using isolation-free imaging flow cytometry (IFCM). Healthy individuals' urine was used to investigate CD9+ HLA-class-I+ uEV quantification using IFCM, time-resolved fluoroimmunoassay (TR-FIA), and immunogold staining cryo-electron microscopy (cryo-EM). Culture-derived CD9+ HLA-class-I+ EVs were spiked into the urine to investigate urine matrix effects on uEV HLA detection. Deceased donor kidneys and peritumoral kidney tissue were used for HLA class I detection with histochemistry. Results: The concentrations of CD9+ HLA-A2+ EVs in both donor and recipient urine approached the negative (detergent-treated) control levels for IFCM and were significantly lower than those observed in donor plasma. In parallel, universal HLA class I+ uEVs were similarly undetectable in the urine and uEV isolates compared with plasma, as verified by IFCM, TR-FIA, and cryogenic electron microscopy. Culture supernatant containing HLA class I+ vesicles from B, T, and human proximal tubule cells were spiked into the urine, and these EVs remained stable at 37°C for 8 hours. Immunohistochemistry revealed that HLA class I was predominantly expressed on the basolateral side of renal tubules, with limited expression on their urine/apical side. Conclusion: The detection of donor-specific uEVs is hindered by the limited release of HLA class I+ EVs from the kidney into the urine, primarily due to the polarized HLA class I expression on renal tubules. Identifying donor-specific uEVs requires further advancements in recognizing transplant-specific uEVs and urine-associated markers.

Identification and validation of novel breed-specific biomarker for the purpose of village chicken authentication using genomics approaches.

Local village chicken, or "Ayam kampung" as it's known in Malaysia, is considered a premium chicken breed with a higher price than other chicken breeds. As a result of their comparable appearances and sizes, colored broiler chickens are often sold as village chickens, which is a form of food fraud that can result in a 3- to 4-fold rise in profit. Therefore, developing a breed-specific authentication method is crucial for preventing food fraud in the poultry industry. This study aims to investigate the genetic diversity of village chickens from other commercial chicken breed populations available in the market (broiler [Cobb], colored broiler [Hubbard], and layer [DeKalb]) to identify breed-specific DNA fragments as biomarkers for village chicken authentication. The Whole-genome sequencing and mutation calling of 12 chickens (3 chickens/breed) led to the identification of a total of 73,454,654 single nucleotide polymorphisms (SNP) and 8,762,338 insertion and deletions (InDel) variants, with more variants detected in the village chicken population (6,346,704 SNPs; 752,408 InDels) compared to commercial breeds. Therefore, this study revealed that village chickens were more genetically variable compared to other breeds in Malaysia. Furthermore, the breed-specific genomic region located on chromosome 1 (1:84,405,652) harboring SNP (C-T) with high discrimination power was discovered and validated which can be considered as a novel breed-specific biomarker to develop a method for accurate authentication of village chickens in Malaysia. This authentication method offers potentialw applications in the chicken industry and food safety.

ELF5: A Molecular Clock for Breast Aging and Cancer Susceptibility.

Breast cancer is predominantly an age-related disease, with aging serving as the most significant risk factor, compounded by germline mutations in high-risk genes like BRCA1/2. Aging induces architectural changes in breast tissue, particularly affecting luminal epithelial cells by diminishing lineage-specific molecular profiles and adopting myoepithelial-like characteristics. ELF5 is an important transcription factor for both normal breast and breast cancer development. This review focuses on the role of ELF5 in normal breast development, its altered expression throughout aging, and its implications in cancer. It discusses the lineage-specific expression of ELF5, its regulatory mechanisms, and its potential as a biomarker for breast-specific biological age and cancer risk.

Organophosphorus and carbamate pesticides: Molecular toxicology and laboratory testing.

Population and food requirements are increasing daily throughout the world. To fulfil these requirements application of pesticides is also increasing. Organophosphorous (OP) and Organocarbamate (OC) compounds are widely used pesticides. These pesticides are used for suicidal purposes too. Both inhibit Acetylcholinesterase (AChE) and cholinergic symptoms are mainly used for the diagnosis of pesticide poisoning. Although the symptoms of the intoxication of OP and OC are similar, recent research has described different targets for OP and OC pesticides. Researchers believe the distinction of OP/OC poisoning will be beneficial for the management of pesticide exposure. OP compounds produce adducts with several proteins. There is a new generation of OP compounds like glyphosate that do not inhibit AChE. Therefore, it's high time to develop biomarkers that can distinguish OP poisoning from OC poisoning.

Utility of promoter hypermethylation in malignant risk stratification of intraductal papillary mucinous neoplasms.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs), a type of cystic pancreatic cancer (PC) precursors, are increasingly identified on cross-sectional imaging and present a significant diagnostic challenge. While surgical resection of IPMN-related advanced neoplasia, i.e., IPMN-related high-grade dysplasia or PC, is an essential early PC detection strategy, resection is not recommended for IPMN-low-grade dysplasia (LGD) due to minimal risk of carcinogenesis, and significant procedural risks. Based on their promising results in prior validation studies targeting early detection of classical PC, DNA hypermethylation-based markers may serve as a biomarker for malignant risk stratification of IPMNs. This study investigates our DNA methylation-based PC biomarker panel (ADAMTS1, BNC1, and CACNA1G genes) in differentiating IPMN-advanced neoplasia from IPMN-LGDs. METHODS: Our previously described genome-wide pharmaco-epigenetic method identified multiple genes as potential targets for PC detection. The combination was further optimized and validated for early detection of classical PC in previous case-control studies. These promising genes were evaluated among micro-dissected IPMN tissue (IPMN-LGD: 35, IPMN-advanced neoplasia: 35) through Methylation-Specific PCR. The discriminant capacity of individual and combination of genes were delineated through Receiver Operating Characteristics curve analysis. RESULTS: As compared to IPMN-LGDs, IPMN-advanced neoplasia had higher hypermethylation frequency of candidate genes: ADAMTS1 (60% vs. 14%), BNC1 (66% vs. 3%), and CACGNA1G (25% vs. 0%). We observed Area Under Curve (AUC) values of 0.73 for ADAMTS1, 0.81 for BNC1, and 0.63 for CACNA1G genes. The combination of the BNC1/ CACNA1G genes resulted in an AUC of 0.84, sensitivity of 71%, and specificity of 97%. Combining the methylation status of the BNC1/CACNA1G genes, blood-based CA19-9, and IPMN lesion size enhanced the AUC to 0.92. CONCLUSION: DNA-methylation based biomarkers have shown a high diagnostic specificity and moderate sensitivity for differentiating IPMN-advanced neoplasia from LGDs. Addition of specific methylation targets can improve the accuracy of the methylation biomarker panel and enable the development of noninvasive IPMN stratification biomarkers.

Identification of Potential Sex-Specific Biomarkers in Pigs with Low and High Intramuscular Fat Content Using Integrated Bioinformatics and Machine Learning.

Intramuscular fat (IMF) content is a key determinant of pork quality. Controlling the genetic and physiological factors of IMF and the expression patterns of various genes is important for regulating the IMF content and improving meat quality in pig breeding. Growing evidence has suggested the role of genetic factors and breeds in IMF deposition; however, research on the sex factors of IMF deposition is still lacking. The present study aimed to identify potential sex-specific biomarkers strongly associated with IMF deposition in low- and high-IMF pig populations. The GSE144780 expression dataset of IMF deposition-related genes were obtained from the Gene Expression Omnibus. Initially, differentially expressed genes (DEGs) were detected in male and female low-IMF (162 DEGs, including 64 up- and 98 down-regulated genes) and high-IMF pigs (202 DEGs, including 147 up- and 55 down-regulated genes). Moreover, hub genes were screened via PPI network construction. Furthermore, hub genes were screened for potential sex-specific biomarkers using the least absolute shrinkage and selection operator machine learning algorithm, and sex-specific biomarkers in low-IMF (troponin I (TNNI1), myosin light chain 9(MYL9), and serpin family C member 1(SERPINC1)) and high-IMF pigs (CD4 molecule (CD4), CD2 molecule (CD2), and amine oxidase copper-containing 2(AOC2)) were identified, and then verified by quantitative real-time PCR (qRT-PCR) in semimembranosus muscles. Additionally, the gene set enrichment analysis and single-sample gene set enrichment analysis of hallmark gene sets were collectively performed on the identified biomarkers. Finally, the transcription factor-biomarker and lncRNA-miRNA-mRNA (biomarker) networks were predicted. The identified potential sex-specific biomarkers may provide new insights into the molecular mechanisms of IMF deposition and the beneficial foundation for improving meat quality in pig breeding.

The Promise of Epigenetics Research in the Treatment of Appendiceal Neoplasms.

Appendiceal cancers (AC) are a rare and heterogeneous group of malignancies. Historically, appendiceal neoplasms have been grouped with colorectal cancers (CRC), and treatment strategies have been modeled after CRC management guidelines due to their structural similarities and anatomical proximity. However, the two have marked differences in biological behavior and treatment response, and evidence suggests significant discrepancies in their respective genetic profiles. In addition, while the WHO classification for appendiceal cancers is currently based on traditional histopathological criteria, studies have demonstrated that histomorphology does not correlate with survival or treatment response in AC. Due to their rarity, appendiceal cancers have not been studied as extensively as other gastrointestinal cancers. However, their incidence has been increasing steadily over the past decade, making it crucial to identify new and more effective strategies for detection and treatment. Recent efforts to map and understand the molecular landscape of appendiceal cancers have unearthed a wealth of information that has made it evident that appendiceal cancers possess a unique molecular profile, distinct from other gastrointestinal cancers. This review focuses on the epigenetic landscape of epithelial appendiceal cancers and aims to provide a comprehensive overview of the current state of knowledge of epigenetic changes across different appendiceal cancer subtypes, highlighting the challenges as well as the promise of employing epigenetics in the quest for the detection of biomarkers, therapeutic targets, surveillance markers, and predictors of treatment response and survival in epithelial appendiceal neoplasms.

Clinical Value of Circulating microRNAs in Diagnosis and Prognosis of Pancreatic Cancer: A Systematic Review.

Pancreatic cancer (PC) is one of the most common cancers and has a high mortality rate due to high invasiveness and rapid progression. Microribonucleic acid (microRNA) plays an essential role in diagnosing PC in the early stages, which improves the five-year survival rate. This systematic review aims to highlight the different subtypes of serum and plasma microRNAs and panel-based assays of microRNAs and how they play a crucial role in the diagnosis and prognosis of PC as a high-sensitive and specific novel biomarker. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines, an in-depth search was performed by using regular keywords and major Medical Subject Heading (MeSH) keywords in PubMed (MEDLINE), PubMed Central, Google Scholar, Science Direct, and Cochrane Library for articles related to this topic and published between 2013 and 2023, up to April 18, 2023. Further eligibility criteria and quality assessment tools were employed to assess the risk of bias, and 13 articles were finalized to be used in this review. The chosen articles included five cross-sectional studies, six systematic reviews and meta-analyses, and two literature reviews. This review provides strong evidence of the usage of microRNA for early diagnosis. It can also be used to exclude differential diagnoses of other diseases, and its prognostic value for determining metastasis and therapeutic efficacy in PC patients. Also, combining microRNA panels with carbohydrate antigen 19.9 (CA19-9) improves the sensitivity and specificity of microRNA as a biomarker.

New Scope of Targeted Therapies in Lung Carcinoma.

Lung Cancer (LC) is the leading cause of cancer deaths worldwide. Recent research has also shown LC as a genomic disease, causing somatic mutations in the patients. Tests related to mutational analysis and genome profiles have lately expanded significantly in the genetics/genomics field of LC. This review summarizes the current knowledge about different signalling pathways of LC based on the clinical impact of molecular targets. It describes the main molecular pathways and changes involved in the development, progression, and cellular breakdown of LC and molecular changes. This review focuses on approved and targeted experimental therapies such as immunotherapy and clinical trials that examine the different targeted approaches to treating LC. We aim to clarify the differences in the extent of various genetic mutations in DNA for LC patients. Targeted molecular therapies for LC can be continued with advanced racial differences in genetic changes, which have a significant impact on the choice of drug treatment and our understanding of the profile of drug susceptibility/ resistance. The most relevant genes described in this review are EGFR, KRAS, MET, BRAF, PIK3CA, STK11, ERBB3, PTEN, and RB1. Combined research efforts in this field are required to understand the genetic difference in LC outcomes in the future.

Exploring Plausible Therapeutic Targets for Alzheimer's Disease using Multi-omics Approach, Machine Learning and Docking.

The progressive deterioration of neurons leads to Alzheimer's disease (AD), and developing a drug for this disorder is challenging. Substantial gene/transcriptome variability from multiple cell types leads to downstream pathophysiologic consequences that represent the heterogeneity of this disease. Identifying potential biomarkers for promising therapeutics is strenuous due to the fact that the transcriptome, epigenetic, or proteome changes detected in patients are not clear whether they are the cause or consequence of the disease, which eventually makes the drug discovery efforts intricate. The advancement in scRNA-sequencing technologies helps to identify cell type-specific biomarkers that may guide the selection of the pathways and related targets specific to different stages of the disease progression. This review is focussed on the analysis of multi-omics data from various perspectives (genomic and transcriptomic variants, and single-cell expression), which provide insights to identify plausible molecular targets to combat this complex disease. Further, we briefly outlined the developments in machine learning techniques to prioritize the risk-associated genes, predict probable mutations and identify promising drug candidates from natural products.

Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene.

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

Identification of subtype specific biomarkers of clear cell renal cell carcinoma using random forest and greedy algorithm.

Suitable biomarkers can be good indicator for cancer subtype. To find biomarkers that can accurately distinguish clear cell renal cell carcinoma (ccRCC) subtypes, we first determined ccRCC subtypes based on the expression of mRNA, miRNA and lncRNA, named clear cell type 1 (ccluster1) and 2 (ccluster2), using three unsupervised clustering algorithms. Besides being associated with the expression pattern derived from the single type of RNA, the differences between subtypes are relevant to the interactions between RNAs. Then, based on ceRNA network, the optimal combination features are selected using random forest and greedy algorithm. Further, in survival-related sub-ceRNA, competing gene pairs centering on miR-106a, miR-192, miR-193b, miR-454, miR-32, miR-98, miR-143, miR-145, miR-204, miR-424 and miR-1271 can also well identify ccluster1 and ccluster2 with prediction accuracy over 92%. These subtype-specific features potentially enhance the accuracy with which machine learning methods predict specific ccRCC subtypes. Simultaneously, the changes of miR-106 and OIP5-AS1 affect cell proliferation and the prognosis of ccluster1. The changes of miR-145 and FAM13A-AS1 in ccluster2 have an effect on cell invasion, apoptosis, migration and metabolism function. Here miR-192 displays a unique characteristic in both subtypes. Two subtypes also display notable differences in diverse pathways. Tumors belonging to ccluster1 are characterized by Fc gamma R-mediated phagocytosis pathway that affects tissue remodeling and repair, whereas those belonging to ccluster2 are characterized by EGFR tyrosine kinase inhibitor resistance pathway that participates in regulation of cell homeostasis. In conclusion, identifying these gene pairs can shed light on therapeutic mechanisms of ccRCC subtypes.

Current Insights into Atopic March.

The incidence of allergic diseases is increasing, and research on their epidemiology, pathophysiology, and the prevention of onset is urgently needed. The onset of allergic disease begins in infancy with atopic dermatitis and food allergy and develops into allergic asthma and allergic rhinitis in childhood; the process is defined as "atopic march". Atopic march is caused by multiple immunological pathways, including allergen exposure, environmental pollutants, skin barrier dysfunction, type 2 inflammation, and oxidative stress, which promote the progression of atopic march. Using recent evidence, herein, we explain the involvement of allergic inflammatory conditions and oxidative stress in the process of atopic march, its epidemiology, and methods for prevention of onset.

Gender specificity improves the early-stage detection of clear cell renal cell carcinoma based on methylomic biomarkers.

AIM: The two genders are different ranging from the molecular to the phenotypic levels. But most studies did not use this important information. We hypothesize that the integration of gender information may improve the overall prediction accuracy. MATERIALS & METHODS: A comprehensive comparative study was carried out to test the hypothesis. The classification of the stages I + II versus III + IV of the clear cell renal cell carcinoma samples was formulated as an example. RESULTS & CONCLUSION: In most cases, female-specific model significantly outperformed both-gender model, as similarly for the male-specific model. Our data suggested that gender information is essential for building biomedical classification models and even a simple strategy of building two gender-specific models may outperform the gender-mixed model.